Analysis on Ethical Problems of Artificial Intelligence Technology

Li, Guiqin; Deng, Xuechao; Chen, Feng

doi:10.1145/3341042.3341057

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…Ethics is embedded in the design and development process of online trading. A human-centered, ethical AI should be designed and developed to be consistent with the values and ethical principles of the online communities it affects (Li, Deng, et al, 2019;Wing et al, 2021). Interpretability is needed to build consumer confidence in AI disruptive technologies in the electronics market, promoting safer practices and broader social adoption (Lauterbach, 2019).…”

Section: Ethical Challengesmentioning

confidence: 99%

Uncovering the Dark Side of Artificial Intelligence in Electronic Markets

Xing,

Yu,

Zhang

et al. 2023

Journal of Organizational and End User Computing

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The dark sides of artificial intelligence (AI) have attracted immense attention in recent years. This study produces a synthesis of current research on six dark sides of AI in electronic markets through a systematic literature review. The authors searched five different databases and summarized the dark sides of AI in electronic markets from six aspects: privacy concerns, security issues, ethical challenges, criminals and terrorists enabled by AI, trust issues between humans and machines, and AI biases. The literature review presented in this study has provided a rigorous and structured overview of research on AI's dark sides in the electronic markets through a combination of quantitative and qualitative analysis of the AI literature. As AI has made rich contributions to a variety of applications in electronic markets, special care should be taken regarding the dark side of AI. Governments and policymakers are recommended to establish legislation to ensure that AI-powered innovation and implementation are beneficial to the social good while limiting the threats caused by the dark side of AI.

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Section: Ethical Challengesmentioning

confidence: 99%

Uncovering the Dark Side of Artificial Intelligence in Electronic Markets

Xing,

Yu,

Zhang

et al. 2023

Journal of Organizational and End User Computing

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“…Although AI can increase the feasibility of developing truly personalized systems, there are ethical issues that developers grapple with. These include, but are not limited to, transparency (Yu and Alì, 2019 ), privacy (Chowdhary, 2020 ), safety and performance (Behera et al, 2022 ), accessibility to artificial intelligence (Morris, 2020 ), moral agency (Swanepoel, 2021 ), biases stemming from data collection process, data, and algorithm (Li et al, 2019 ), threats to human autonomy (Sankaran et al, 2020 ), environmental and ecological challenges arising from hardware and energy consumptions required to develop and operate AI technologies (Li et al, 2019 ), liability issues in event of a damage or harm (Cerka et al, 2015 ), and social acceptability (Morris, 2020 ).…”

Section: Role Of Artificial Intelligencementioning

confidence: 99%

“…The ethical issues in AI technologies are caused by limitations in the technology itself [e.g., the use of black-box algorithms such as deep learning, random forest, support vector machines which are less explainable but provide high accuracy precision (Chang, 2020 )], insufficiencies in AI regulations and policy, and insufficiency of existing ethical design principles (Li et al, 2019 ). Also, true personalization requires detailed information about the user and hence users must be willing to reveal personal information to benefit from it (Kobsa, 2002 ).…”

Section: Role Of Artificial Intelligencementioning

confidence: 99%

Mitigating Issues With/of/for True Personalization

Oinas-Kukkonen

Pohjolainen

Agyei

2022

Front. Artif. Intell.

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A common but false perception persists about the level and type of personalization in the offerings of contemporary software, information systems, and services, known as Personalization Myopia: this involves a tendency for researchers to think that there are many more personalized services than there genuinely are, for the general audience to think that they are offered personalized services when they really are not, and for practitioners to have a mistaken idea of what makes a service personalized. And yet in an era, which mashes up large amounts of data, business analytics, deep learning, and persuasive systems, true personalization is a most promising approach for innovating and developing new types of systems and services—including support for behavior change. The potential of true personalization is elaborated in this article, especially with regards to persuasive software features and the oft-neglected fact that users change over time.

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“…This is already attempted to address but is still in one's infancy. For example, the research of Li et al [27] defines three groups of interest to be aware of if developing an AD focused framework: automotive manufacturers, consumers, and governments. Also, research contributions like the ones of Borenstein et al [28] or Poon and Sung [29] proof that there are governmental discussions about the legal liability of software developers and designers for violations of the autonomous framework.…”

Section: State-of-the-artmentioning

confidence: 99%

A Moral Consensus Mechanism for Autonomous Driving: Towards a Law-compliant Basis of Logic Programming

Wanner¹,

Herm²,

Langer³

et al. 2020

WI2020 Zentrale Tracks

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Research into autonomous vehicles is making progress. While implementation is progressing through machine learning and efficient sensor technology, one key challenge remains dealing with moral disputes. In general, traffic requires for moral decisions that might even decide on the life or death of participants. While people make intuitive decisions in accidents, a decision of an autonomous vehicle is made already at the programming stage. Thus, a concrete handling for implementation is needed. Due to a lack of legislation, this is still missing and prevents car manufacturers from a practical solution. The paper at hand addresses this problem by presenting a consensus mechanism, combining moral convictions, legislation, and programming guidelines. Based on a study of dilemma situations, moral principles of the 'correct action' of autonomous vehicles are derived. Of four principles, we confirm one, reject two, and propose one for further research investigation to form a basis for jurisdictions.

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Analysis on Ethical Problems of Artificial Intelligence Technology

Cited by 6 publications

References 12 publications

Uncovering the Dark Side of Artificial Intelligence in Electronic Markets

Uncovering the Dark Side of Artificial Intelligence in Electronic Markets

Mitigating Issues With/of/for True Personalization

A Moral Consensus Mechanism for Autonomous Driving: Towards a Law-compliant Basis of Logic Programming

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